Beginner Lessons

Authoring Interactive, Shareable AI Evaluation Reports with Zeno // Alex Cabrera // LLMs III Talk

Evaluating LLMs for AI Risk // Finn Howell // LLMs in Production Conference III Lightning Talk

Speed and Sensibility: Balancing Latency and UX in Generative AI // Julia Kroll // LLMs III LT

Building RAG-based LLM Applications for Production // Philipp Moritz & Yifei Feng // LLMs III Talk

Deploying LLMs on Structured Data Tasks: Lessons from the Trenches // Laurel Orr // LLMs III Talk

Synthetic Data for Robust LLM Application Evaluation // Shahul Es // LLMs III Lightning Talk

Assess the Value and Feasibility of LLM Use Cases with a Checklist // Rens Dimmendaal & Eva Bosma

Current State of LLMs in Production // Apurva Misra // LLMs III Lightning Talk

The Future of Feature Stores and Platforms // Mike Del Balso & Josh Wills // MLOps Podcast # 186

Lessons on Data Teams Leadership // Luigi Patruno // MLOps Podcast #185

Building Context-Aware Reasoning Applications with LangChain and LangSmith // Harrison Chase // LLM3

Insights on Real-Time ML and Its Impact on Traffic Predictions // Ketan Umare // Podcast clip #183

Rituals & Best Practices // Jean Machado, Meghana Satish, Olivia Houghton, Theodore Meynard // clip

Translating Business Goals into Product Decisions // Richa Sachdev // MLOps Podcast #184

Observability for LLMs // Phillip Carter // LLMs in Production Conference Lightning Talk 4

AI Safety: Balancing Control and Equalization? // Kyle Harrison // MLOps Podcast 181 clip

Maximizing the Potential of Deep Learning in Tabular Data Analysis // Sachin Abeywardana //#180 clip

What Drives GenAI Development in the Next 3 Years // Euro Beinat // LLMs in Production Conference 3

Fireside Chat with LLM Startups // LLMs in Production Conference 3

Finetuning Open-Source LLMs // Sebastian Raschka // LLMs in Production Conference 3 Keynote 1

MLOps@GetYourGuide // Jean Machado, Meghana Satish, Olivia Houghton, Theodore Meynard// Podcast #182

#mlops #machinelearning #ai #llm

#mlops #ai #machinelearning #llm

#mlops #ai #machinelearning #llm

#mlops #ai #machinelearning #llm

Harnessing User Feedback for ML Platform Updates // Stephen Batifol // MLOps Podcast #178 clip

LLM Security //Raahul Dutta & Uri Shamay & Sankalp Gilda // Mini Summit #1

Building an ML Platform: Insights, Community, and Advocacy // Stephen Batifol // MLOps Podcast #178

Introduction to QA bots with RAGs and LLMs

#mlops #ai #machinelearning #openai

#mlops #ai #machinelearning

#mlops #ai #llm #machinelearning

#mlops #ai #llm #machinelearning

The Quest for a Unified MLOps Infrastructure // Lamia Youseff // MLOps Podcast # 175 clip

From Virtualization to AI Integration // Lamia Youseff // MLOps Podcast # 175

Leveraging Open Source LLMs for Optimal Results // LLMs in Production Conference Part II clip

Building RedPajama // Vipul Ved Prakash // LLMs in Production Conference Part 2

LLM-based Feature Extraction for Operational Optimization // Xin Lian // LLMs in Prod Con Part 2

Fireside Chat - The Future of LLMs // David Hershey & Daniel Jeffries // LLMs in Prod Con Part 2

Preemption Chaos and Optimizing Server Startup // Bradley Heilbrun // LLMs in Prod Conference Part 2

Using LLMs to Power Consumer Search at Scale // Aravind Srinivas // LLMs in Prod Conference Part 2

Enabling Defense Missions with Local LLMs // Gerred Dillon // LLMs in Production Conference Part 2

LLM XGBoost - Can a Fine-Tuned LLM Beat XGBoost on Tabular Data? // Sebastian Cattes // LLMs Part 2

Evolving AI Governance for an LLM World // Diego Oppenheimer // LLMs in Production Conference Part 2

From an API to a Chat GPT Plugin // Mathieu Bastian // LLMs in Production Conference Part 2

Everything We've Been Taught About ML is Wrong // Emmanuel Ameisen // LLMs in Prod Con Part 2

Language Models: Developing Apps - Challenges & Solutions // Barak Turovsky /MLOps Podcast #169 clip

From Experiment to Prompt Tracking in MLOps // Piotr Niedźwiedź // MLOps Podcast #168 clip